Current object detection algorithms are focused on robustly detects the target object. Even the detection window is not precisely overlapping the object, the object detector can still response with a high detection score. It contradicts with some applications in which want as accurate localization as possible.
Standard sliding window based object detection requires dense classifier evaluation on densely sampled locations in scale space in order to achieve an accurate localization. To avoid such dense evaluation, selective search based algorithms only evaluate the classifier on a small subset of object proposals. Notwithstanding the demonstrated success, object proposals do not guarantee perfect overlap with the object, leading to a suboptimal detection accuracy.